Triple
T10211471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rogue Lawyer |
E242337
|
entity |
| Predicate | follows |
P134
|
FINISHED |
| Object | Gray Mountain |
E320680
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Gray Mountain | Statement: [Rogue Lawyer, follows, Gray Mountain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gray Mountain Context triple: [Rogue Lawyer, follows, Gray Mountain]
-
A.
Gray Mountain
chosen
Gray Mountain is a legal thriller novel by John Grisham that follows a young lawyer uncovering corruption and environmental crimes in a small Appalachian coal town.
-
B.
Ryan Mountain
Ryan Mountain is a prominent peak in Joshua Tree National Park, California, known for its panoramic desert views and popularity among hikers.
-
C.
Regal Mountain
Regal Mountain is a prominent high peak in Alaska’s Wrangell Mountains, known for its extensive glaciation and remote, rugged terrain.
-
D.
West Mountain
West Mountain is a ski and recreation area in the Adirondack region of upstate New York, offering downhill skiing, snowboarding, and year-round outdoor activities.
-
E.
West Mountain
West Mountain is one of the main ski slopes within the Rusutsu Resort in Hokkaido, Japan, offering a variety of runs for skiers and snowboarders.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa22071c819095febd18dd607978 |
completed | April 6, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65e9136bc8190b35685376da7007e |
completed | May 2, 2026, 8:29 p.m. |
Created at: April 6, 2026, 11:01 a.m.